Published April 2019 | Version v1
Journal article

On parameter estimation in an in vitro compartmental model for drug-induced enzyme production in pharmacotherapy

  • 1. Charles University, Faculty of Pharmacy in Hradec Králové (Czech Republic)
  • 2. Czech Academy of Sciences, Institute of Computer Science (Czech Republic)
  • 3. University of South Bohemia in České Budějovice, Institute of Complex Systems, South Bohemian Research Center of Aquaculture and Biodiversity of Hydrocenoses, Faculty of Fisheries and Protection of Waters (Czech Republic)

Description

A pharmacodynamic model introduced earlier in the literature for in silico prediction of rifampicin-induced CYP3A4 enzyme production is described and some aspects of the involved curve-fitting based parameter estimation are discussed. Validation with our own laboratory data shows that the quality of the fit is particularly sensitive with respect to an unknown parameter representing the concentration of the nuclear receptor PXR (pregnane X receptor). A detailed analysis of the influence of that parameter on the solution of the model's system of ordinary differential equations is given and it is pointed out that some ingredients of the analysis might be useful for more general pharmacodynamic models. Numerical experiments are presented to illustrate the performance of related parameter estimation procedures based on least-squares minimization.

Additional details

Identifiers

Publishing Information

Journal Title
Applications of Mathematics (Praha)
Journal Volume
64
Journal Issue
2
Journal Page Range
p. 253-277
ISSN
0862-7940

INIS

Country of Publication
Czech Republic
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
54062553
Subject category
S97: MATHEMATICAL METHODS AND COMPUTING; S62: RADIOLOGY AND NUCLEAR MEDICINE;
Descriptors DEI
CHEMOTHERAPY; COMPUTERIZED SIMULATION; DIFFERENTIAL EQUATIONS; IN VITRO; LEAST SQUARE FIT; MINIMIZATION
Descriptors DEC
EQUATIONS; MATHEMATICAL SOLUTIONS; MAXIMUM-LIKELIHOOD FIT; MEDICINE; NUMERICAL SOLUTION; OPTIMIZATION; SIMULATION; THERAPY

Optional Information

Copyright
Copyright (c) 2019 Mathematical Institute, Academy of Sciences of Cz